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Record W3041568807 · doi:10.1128/aac.00894-20

Adding Insult to Injury: Mechanistic Basis for How AmpC Mutations Allow Pseudomonas aeruginosa To Accelerate Cephalosporin Hydrolysis and Evade Avibactam

2020· article· en· W3041568807 on OpenAlexafffund
Cole Slater, Judith L. Winogrodzki, Pablo A. Fraile-Ribot, Antonio Oliver, Mazdak Khajehpour, Brian L. Mark

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsCephalosporinPseudomonas aeruginosaAvibactamMicrobiologyBiologyChemistryAntibioticsBacteriaGenetics

Abstract

fetched live from OpenAlex

is a leading cause of nosocomial infections worldwide and notorious for its broad-spectrum resistance to antibiotics. A key mechanism that provides extensive resistance to β-lactam antibiotics is the inducible expression of AmpC β-lactamase. Recently, a number of clinical isolates expressing mutated forms of AmpC have been found to be clinically resistant to the antipseudomonal β-lactam-β-lactamase inhibitor (BLI) combinations ceftolozane-tazobactam and ceftazidime-avibactam. Here, we compare the enzymatic activity of wild-type (WT) AmpC from PAO1 to those of four of these reported AmpC mutants, bearing mutations E247K (a change of E to K at position 247), G183D, T96I, and ΔG229-E247 (a deletion from position 229 to 247), to gain detailed insights into how these mutations allow the circumvention of these clinically vital antibiotic-inhibitor combinations. We found that these mutations exert a 2-fold effect on the catalytic cycle of AmpC. First, they reduce the stability of the enzyme, thereby increasing its flexibility. This appears to increase the rate of deacylation of the enzyme-bound β-lactam, resulting in greater catalytic efficiencies toward ceftolozane and ceftazidime. Second, these mutations reduce the affinity of avibactam for AmpC by increasing the apparent activation barrier of the enzyme acylation step. This does not influence the catalytic turnover of ceftolozane and ceftazidime significantly, as deacylation is the rate-limiting step for the breakdown of these antibiotic substrates. It is remarkable that these mutations enhance the catalytic efficiency of AmpC toward ceftolozane and ceftazidime while simultaneously reducing susceptibility to inhibition by avibactam. Knowledge gained from the molecular analysis of these and other AmpC resistance mutants will, we believe, aid in the design of β-lactams and BLIs with reduced susceptibility to mutational resistance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.262
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations50
Published2020
Admission routes2
Has abstractyes

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